Robot cleaner and method for controlling the same

ABSTRACT

Disclosed is a method for controlling a robot cleaner including acquiring, by a camera, an image, irradiating, by a light source, light toward a location the same as a location where the acquired image is captured, receiving, by a sensor, the light irradiated from the light source and reflected on an object, processing an image received from the sensor to contain a distance value of an individual location, and supplementing the image received from the sensor with the image captured by the camera when a singularity is found, wherein distance values calculated in adjacent portions are discontinuous at the singularity.

TECHNICAL FIELD

The present disclosure relates to a robot cleaner and a method forcontrolling the same, and more particularly, to a robot cleaner and amethod for controlling the same capable of accurately identifying anobstacle using a depth image and a 2-dimensional image and avoiding theobstacle.

BACKGROUND ART

In general, robots have been developed for industrial use and have beenresponsible for a part of factory automation. In recent years, fields towhich robots are applied have been further expanded, so that medicalrobots, aerospace robots, and the like have been developed, andhousehold robots that may be used in general homes are also being made.

A representative example of the household robot is a robot cleaner,which is a kind of home appliance that sucks surrounding dust or foreignmatter to perform cleaning while traveling by itself in a certainregion. Such a robot cleaner is generally equipped with a rechargeablebattery and an obstacle sensor for avoiding an obstacle while traveling,so that the robot cleaner may perform the cleaning while traveling byitself.

Korean Patent Publication Application No. 10-2014-0011216, which is aprior art, discloses a technology of capturing a floor image andautomatically sensing whether a material of a floor is a materialsimilar to a carpet or the like or a material similar to a floor paperor the like. However, in the prior art, it is difficult to sense anobstacle that is difficult to be sensed through the image capturing,particularly, a thin obstacle such as a wire and the like.

DISCLOSURE OF INVENTION Technical Problem

The present disclosure is to solve the above problems, and the presentdisclosure is to provide a robot cleaner and a method for controllingthe same capable of accurately sensing an obstacle by supplementing anunclear portion in a captured depth image with a camera image.

In addition, the present disclosure is to provide a robot cleaner and amethod for controlling the same capable of determining a thin obstaclesuch as a wire and avoiding the corresponding obstacle.

Solution to Problem

The present disclosure provides a robot cleaner and a method forcontrolling the same that may supplement a portion in a depth image inwhich it is difficult to identify whether an obstacle is recognizedbecause of noise or diffused reflection/absorption resulted from a smallsize with color or brightness information of an IR image or an RGBimage, thereby avoiding an obstacle.

The present disclosure acquires brightness or color information of somesensed points in the depth image from the IR image or the RGB image,then expands the sensed points through the brightness or colorinformation of the acquired points, and then combines the expandedpoints with a slightly sensed depth image detection result to secureenough volume to be recognized as the obstacle.

The present disclosure provides a method for controlling a robot cleanerincluding acquiring, by a camera, an image, irradiating, by a lightsource, light toward a location the same as a location where theacquired image is captured, receiving, by a sensor, the light irradiatedfrom the light source and reflected on an object, processing an imagereceived from the sensor to contain a distance value of an individuallocation, and supplementing the image received from the sensor with theimage captured by the camera when a singularity is found, whereindistance values calculated in adjacent portions are discontinuous at thesingularity.

In addition, the present disclosure provides a robot cleaner including acamera for acquiring an image, a light source for irradiating lighttoward a location the same as a location where the acquired image iscaptured, a sensor for sensing that the light irradiated from the lightsource is reflected, and a controller that processes an image using thelight sensed by the sensor to calculate a distance value of anindividual location in the corresponding image, wherein the image issupplemented with the image acquired by the camera when a singularity isfound, wherein distance values calculated in adjacent portions arediscontinuous at the singularity.

Advantageous Effects of Invention

According to the present disclosure, the unclear portion in the captureddepth image may be supplemented with the camera image, so that theobstacle may be accurately sensed. Therefore, a sensing accuracy of theobstacle may be improved.

In addition, according to the present disclosure, the thin obstacle suchas the wire may be sensed, so that the robot cleaner may travel whileavoiding the corresponding obstacle, thereby preventing a damage of therobot cleaner.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a perspective view of a robot cleaner according to anembodiment.

FIG. 2 is a plan view of FIG. 1 .

FIG. 3 is a side view of FIG. 1 .

FIG. 4 is a block diagram showing components of a robot cleaneraccording to an embodiment.

FIG. 5 is a control flowchart according to an embodiment.

FIG. 6 is a view comparing images of a sensor and a camera captured awire.

FIG. 7 is a view comparing images of a sensor and a camera captured athin rod.

MODE FOR THE INVENTION

Hereinafter, a preferred embodiment according to the present disclosurethat may specifically realize the above object will be described withreference to the accompanying drawings.

In such process, a size or a shape of a component shown in the drawingsmay be exaggerated for clarity and convenience of description. Moreover,terms specifically defined in consideration of the composition andoperation according to the present disclosure may vary depending on theintention or custom of the user or operator. Definitions of such termsshould be made based on the contents throughout this specification.

Referring to FIGS. 1 to 3 , a robot cleaner 100 performs a function ofcleaning a floor while traveling by itself in a certain region. Thecleaning of the floor referred herein includes sucking dust (includingforeign matter) from the floor or mopping the floor.

The robot cleaner 100 includes a cleaner body 110, a suction unit 120, asensing unit 130, and a dust collection vessel 140.

The cleaner body 110 includes a controller (not shown) for controllingthe robot cleaner 100 and a wheel unit 111 for the traveling of therobot cleaner 100. The robot cleaner 100 may be moved back and forth andleft and right, or rotated by the wheel unit 111.

The wheel unit 111 includes main wheels 111 a and sub-wheels 111 b.

The main wheels 111 a may be respectively arranged on both sides of thecleaner body 110 to rotate in one direction or the other direction inresponse to a control signal of the controller. The main wheels 111 amay be driven independently of each other. For example, the main wheels111 a may be respectively driven by different motors.

The sub-wheels 111 b support the cleaner body 110 together with the mainwheels 111 a, and assist the traveling of the robot cleaner 100 by themain wheels 111 a. Such sub-wheels 111 b may also be arranged in thesuction unit 120 to be described later.

As described above, as the controller controls the driving of the wheelunit 111, the robot cleaner 100 autonomously travels on the floor.

In one example, the cleaner body 110 is equipped with a battery (notshown) that supplies power to the robot cleaner 100. The battery may berechargeable and detachable from a bottom face of the cleaner body 110.

The suction unit 120 is disposed to protrude from one side of thecleaner body 110 and sucks air containing dust. The one side may be aside on which the cleaner body 110 travels in a forward direction F,that is, a front side of the cleaner body 110.

The suction unit 120 may be detachably coupled to the cleaner body 110.When the suction unit 120 is separated from the cleaner body 110, a mopmodule (not shown) may be detachably coupled to the cleaner body 110 byreplacing the separated suction unit 120. Therefore, when a user wantsto remove the dust from the floor, the user may mount the suction unit120 on the cleaner body 110. In addition, when the user wants to mop thefloor, the user may mount the mop module on the cleaner body 110.

The sensing unit 130 is disposed on the cleaner body 110. As shown, thesensing unit 130 may be disposed on the one side of the cleaner body 110where the suction unit 120 is located, that is, the front side of thecleaner body 110.

The sensing unit 130 may be disposed to overlap the suction unit 120 ina vertical direction of the cleaner body 110. The sensing unit 130 isdisposed above the suction unit 120 to sense an obstacle, a terrainobject, or the like located in front of the robot cleaner such that thesuction unit 120 located at the frontmost portion of the robot cleaner100 does not collide with the obstacle.

The sensing unit 130 additionally performs another sensing function inaddition to such sensing function. This will be described in detaillater.

In FIG. 4 below, an embodiment associated with components of the robotcleaner 100 will be described.

The robot cleaner 100 according to an embodiment of the presentdisclosure may include at least one of a communication device 1100, aninput device 1200, a driver 1300, a sensing unit 1400, an output device1500, a power unit 1600, a memory 1700, and a controller 1800, or acombination thereof.

In this connection, the components shown in FIG. 4 are not essential, sothat a robot cleaner having more or fewer components than that may beimplemented. Hereinafter, each of the component will be described.

First, the power supply 1600 includes a battery that may be charged byan external commercial power source to supply power into the mobilerobot.

The power supply 1600 may supply driving power to each of the componentsincluded in the mobile robot, thereby supplying operation power requiredfor the mobile robot to travel or perform a specific function.

In this connection, the controller 1800 may sense a remaining power ofthe battery, and control the mobile robot to move to the charging deviceconnected to the external commercial power source when the remainingpower is insufficient, thereby charging the battery by receivingcharging current from the charging device. The battery may be connectedto a battery sensor, so that the remaining power of the battery and astate of charge may be transmitted to the controller 1800. The outputdevice 1500 may display the remaining power of the battery on a screenby the controller.

The battery may be located at a lower portion of a center of the robotcleaner or may be located on one of left and right sides. In the lattercase, the mobile robot may further include a counterweight to eliminateweight bias of the battery.

The controller 1800 plays a role of processing information based on anartificial intelligence technology, which may include at least onemodule that performs at least one of learning of information, inferenceof information, perception of information, and processing of naturallanguage.

The controller 1800 may use a machine learning technology to perform atleast one of the learning, the inference, and the processing of a vastamount of information (big data) such as information stored in thecleaner, surrounding environment information, and information stored inan external communicable storage. In addition, the controller 1800 maypredict (or infer) one or more executable operations of the cleanerusing the information learned using the machine learning technology, andcontrol the cleaner such that an operation with the highest realizationamong the one or more predicted operations is executed.

The machine learning technology is a technology, based on at least onealgorithm, of collecting and learning large-scale information, anddetermining and predicting information based on the learned information.The learning of the information is an operation of quantifying arelationship between information and information by identifyingcharacteristics, rules, and criteria of determination of theinformation, and predicting new data using a quantified pattern.

An algorithm used in the machine learning technology may be an algorithmbased on statistics, and may be, for example, a decision tree that usesa tree structure as a prediction model, an artificial neural networkthat mimics a structure and a function of a neural network of a livingthing, genetic programming based on an evolution algorithm of the livingthing, clustering that distributes observed examples into subsets calledclusters, a Monte Carlo method that calculates function values withprobability through randomly extracted random numbers, and the like.

As a field of the machine learning technology, a deep learningtechnology is a technology of performing at least one of the learning,the determination, and the processing of the information using anartificial neural network (deep neuron network, DNN) algorithm. Theartificial neural network (DNN) may have a structure of connectinglayers with each other and transferring data between the layers. Suchdeep learning technology may learn a vast amount of information throughthe artificial neural network (DNN) using a graphic processing unit(GPU) optimized for parallel computation.

The controller 1800 may use training data stored in an external serveror in the memory, and may be equipped with a learning engine thatdetects features for recognizing a predetermined object. In thisconnection, the features for recognizing the object may include a size,a shape, a shadow, and the like of the object.

Specifically, in the controller 1800, when some of images acquiredthrough a camera disposed in the cleaner are input into the learningengine, the learning engine may recognize at least one object or livingthing contained in the input images.

As such, when applying the learning engine to the travel of the cleaner,the controller 1800 may recognize whether an obstacle, such as a chairleg, a fan, or a certain type of balcony gap, that interferes with thetravel of the cleaner exists around the cleaner, so that efficiency andreliability of the cleaner travel may be increased.

In one example, the learning engine as described above may be mounted onthe controller 1800 or on the external server. When the learning engineis mounted on the external server, the controller 1800 may control thecommunication device 1100 to transmit at least one image, which is ananalysis target, to the external server.

The external server may recognize the at least one object or livingthing contained in the corresponding image by inputting the imagetransmitted from the cleaner into the learning engine. In addition, theexternal server may transmit information associated with a recognitionresult back to the cleaner.

In this connection, the information associated with the recognitionresult may include information associated with the number of objectscontained in the image, which is the analysis target, and a name of eachobject.

In one example, the driver 1300 includes a motor, and drives the motorto rotate the left and right main wheels in both directions, therebyturning or moving the body. The driver 1300 may allow the body of themobile robot to move back and forth and left and right, to travel in acurved manner, or to turn in place.

In one example, the input device 1200 receives various control commandsfor the robot cleaner from the user. The input device 1200 may includeat least one button. For example, the input device 1200 may include anidentification button, a setting button, and the like. Theidentification button is a button for receiving a command foridentifying sensing information, obstacle information, locationinformation, and map information from the user. The setting button is abutton for receiving a command for setting the information from theuser.

In addition, the input device 1200 may include an input resetting buttonfor cancelling a previous user input and receiving a user input again, adelete button for deleting a preset user input, a button for setting orchanging an operating mode, a button for receiving a command to returnto the charging device, and the like.

In addition, the input device 1200 may be installed on a top face of themobile robot as a hard key, a soft key, a touch pad, and the like. Inaddition, the input device 1200 may have a form of a touch screentogether with the output device 1500.

In one example, the output device 1500 may be installed on the top faceof the mobile robot. In one example, an installation location or aninstallation form may become different. For example, the output device1500 may display a battery state, a travel scheme, or the like on ascreen.

In addition, the output device 1500 may output information of a statusof an interior of the mobile robot detected by the sensing unit 1400,for example, current status of each component included in the mobilerobot. In addition, the output device 1500 may display information of astatus of an exterior detected by the sensing unit 1400, the obstacleinformation, the location information, the map information, and the likeon the screen. The output device 1500 may be formed as one of a lightemitting diode (LED), a liquid crystal display (LCD), a plasma displaypanel, and an organic light emitting diode (OLED).

The output device 1500 may further include sound output means foraurally outputting an operation process of the mobile robot performed bythe controller 1800 or an operation result. For example, the outputdevice 1500 may output a warning sound to the outside in response to awarning signal generated by the controller 1800.

In one example, the communication device 1100 is connected to a terminaldevice and/or another device located within a specific region (in thisspecification, the term “home appliance” will be used interchangeably)through one of wired, wireless, and satellite communication schemes totransmit and receive signals and data.

In one example, the memory 1700 stores a control program that controlsor drives the robot cleaner and data generated therefrom. The memory1700 may store audio information, image information, the obstacleinformation, the location information, the map information, and thelike. In addition, the memory 1700 may store information associated witha travel pattern.

In one example, the sensing unit 1400 may include an external signalsensor and a cliff sensor.

The external signal sensor may sense an external signal of the mobilerobot. The external signal sensor may be, for example, an infrared raysensor, an ultrasonic sensor, a radio frequency sensor (RF sensor), andthe like.

The mobile robot may identify a location and a direction of a chargingdevice by receiving a guide signal generated by the charging deviceusing the external signal sensor. In this connection, the chargingdevice may transmit the guide signal indicating the direction and adistance such that the mobile robot is able to return. That is, themobile robot may receive the signal transmitted from the charging deviceto determine the current location and set a moving direction to returnto the charging device.

In one example, the cliff sensor may sense the obstacle on the floorthat supports the body of the mobile robot mainly using various types ofoptical sensors.

That is, the cliff sensor is installed on a rear face of the mobilerobot on the floor, but the cliff sensor is able to be installed atdifferent locations based on a type of the mobile robot. The cliffsensor is for sensing the obstacle on the floor by being located on therear face of the mobile robot. The cliff sensor may be an infrared raysensor, an ultrasonic sensor, an RF sensor, a position sensitivedetector (PSD) sensor, and the like equipped with a light emitter and alight receiver like the obstacle sensor.

As an example, one of the cliff sensors may be installed at a frontportion of the mobile robot, and the other two cliff sensors may beinstalled at a relatively rear portion.

For example, the cliff sensor may be the PSD sensor, but may be composedof a plurality of different types of sensors.

The controller 1800 may measure an infrared ray angle between a lightemission signal of an infrared ray emitted by the cliff sensor towardthe ground and a reflection signal received by being reflected by theobstacle to sense the cliff and analyze a depth thereof.

In one example, the controller 1800 may determine whether to pass thecliff based on a ground condition of the cliff sensed using the cliffsensor, and may determine whether to pass the cliff based on thedetermination result. For example, the controller 1800 determineswhether the cliff exists and the depth of the cliff using the cliffsensor, and then passes the cliff only when the reflection signal issensed through the cliff sensor.

As another example, the controller 1800 may use the cliff sensor todetermine a lifting phenomenon of the mobile robot.

The sensing unit 1400 may include a camera 1406. In this connection, thecamera may mean a two-dimensional camera sensor. The camera 1406 isdisposed on one face of the robot cleaner and acquires image informationassociated with a region around the body while moving.

Image data in a predetermined format is generated by converting an imageinput from an image sensor disposed in the camera 1406. The generatedimage data may be stored in the memory 1700.

In one example, the sensing unit 1400 may include a 3-dimensional depthcamera (3D depth camera) that calculates a perspective distance betweenthe robot cleaner and an imaging target. Specifically, the depth cameramay capture a 2-dimensional image associated with the region around thebody, and may generate a plurality of 3-dimensional coordinateinformation corresponding to the captured 2D image.

In an embodiment, the depth camera may include a light source 1402 thatemits light and a sensor 1404 that receives the light from the lightsource 1402, and analyze an image received from the sensor 1404, therebymeasuring a distance between the robot cleaner and the imaging target.Such 3D depth camera may be a 3D depth camera in a time of flight (TOF)scheme.

In another embodiment, the depth camera may include, together with thesensor 1404, the light source 1402 that irradiates an infrared raypattern, that is, an infrared ray pattern emitter. The sensor 1404 maymeasure the distance between the robot cleaner and the imaging target bycapturing a shape of the infrared ray pattern irradiated from theinfrared ray pattern emitter projected onto the imaging target. Such 3Ddepth camera may be a 3D depth camera in an infrared (IR) scheme.

In another embodiment, the depth camera may be formed in a stereo visionscheme in which at least two cameras that acquire the existing2-dimensional images are arranged and at least two images respectivelyacquired from the at least two cameras are combined with each other togenerate the 3-dimensional coordinate information.

Specifically, the depth camera according to the embodiment may include afirst pattern irradiating unit that irradiates light of a first patterndownward toward the front of the body, a second pattern irradiating unitthat irradiates light of a second pattern upward toward the front of thebody, and an image acquisition unit that acquires an image of the frontof the body. Thus, the image acquisition unit may acquire an image of aregion into which the light of the first pattern and the light of thesecond pattern are incident.

FIG. 5 is a control flowchart according to an embodiment. Further, FIG.6 is a view comparing images of a sensor and a camera captured a wire. Aprocess in which the robot cleaner recognizes an obstacle such as a wirein an embodiment will be described with reference to FIGS. 5 and 6 .

While the robot cleaner travels, the camera 1406 may acquire the imageof the region around the robot cleaner (S10). In this connection, thecamera 1406 may provide an image of the robot cleaner viewed from thefront.

The light source 1402 irradiates the light toward a location the same asa location captured by the camera 1406 (S20). In this connection, aplurality of the light sources 1402 may be arranged and the plurality oflight sources may irradiate light with a time difference.

The light irradiated from the light source 1402 is received by thesensor 1404 after being reflected from the object (S30).

Then, information received from the sensor 1404 is processed to containa distance value of an individual location through the controller 1800(S40). That is, the information acquired from the sensor 1404 isinformation illustrating a two-dimensional plane. In this connection,the controller 1800 may calculate the distance value by calculating anarrival time point of the light received by the sensor 1404, and thelike, and allow the information received from the sensor 1404 to containthe distance value of the corresponding location. In one example, thecontroller 1800 may calculate the distance value of each location of theimage in various forms other than the above-described scheme.

Then, the controller 1800 determines whether there is a singularity atwhich distance values calculated in adjacent portions are discontinuousin the corresponding image (S50). In this connection, the adjacentportions may usually mean portions that are arranged close to each otherenough for the distance values to form a single object. That is, whenthe image captured by the sensor 1404 is an image captured from a longdistance, a distance between the adjacent portions may be set relativelysmall. On the other hand, when the captured image is an image capturedat a close distance, the distance between the adjacent portions may beset relatively large.

In one example, whether there are a plurality of singularities insteadof one singularity may also be detected. This is because it may besuspected that a plurality of obstacles are arranged fairly close toeach other when there is one singularity, but it may be expected thatthere is noise or an error in the image acquired by processing theinformation captured by the sensor 1404 when there are the plurality ofsingularities.

For example, the image acquired by processing the information acquiredby the sensor 1404 may be a screen shown in (a) in FIG. 6 . When thewire is placed on the floor, a plurality of singularities are found inpatches in the wire. In this case, it may be determined that there are aplurality of small obstacles based on the information acquired from thesensor 1404. In one example, because a size of each of a plurality ofdivided regions is small, the image acquired by processing theinformation acquired by the sensor 1404 may be ignored as informationresulted from the error and it may be determined that there is no actualobstacle.

In order to solve such problem, in the present embodiment, the imageacquired by processing the information acquired by the sensor 1404 issupplemented using an image captured by the camera as shown (b) in FIG.6 (S60).

The camera 1406 may capture the 2-dimensional image. That is,information of capturing a status of the location acquired by the sensor1404 may be acquired.

In one example, when the camera 1406 is an RGB camera, and when thesingularities are in the same color in S60, disconnected portions havingthe singularities interposed therebetween may be connected to each otherand be determined as the same object. That is, even though theinformation in which there are the disconnected portions having thesingularities interposed therebetween as shown in (a) in FIG. 6 istransmitted, when it is determined that two disconnected portions and asingularity interposed therebetween are in the same color, thedisconnected portions may be supplemented as a single object as shown in(b) in FIG. 6 . The RGB camera acquires information about a color of theobject from the camera. An error in which, even though the disconnectedportions are the single object in the same color, the disconnectedportions are determined as a plurality of objects by the sensor 1404 orare not determined as the object may be prevented.

In one example, when the camera 1406 is an IR camera, and when thesingularities have the same brightness in S60, the disconnected portionshaving the singularities interposed therebetween may be connected toeach other and be determined as the same object. That is, even thoughthe information in which there are the disconnected portions having thesingularities interposed therebetween as shown in (a) in FIG. 6 istransmitted, when it is determined that the two disconnected portionsand the singularity interposed therebetween have the same brightness,the disconnected portions may be supplemented as a single object asshown in (b) in FIG. 6 . The IR camera acquires information about ashape of the object. In this connection, an error in which, even thoughthe disconnected portions may be the single object based on theinformation acquired from the IR camera, the disconnected portions aredetermined as a plurality of objects by the sensor 1404 or are notdetermined as the object may be prevented.

That is, in the present embodiment, information about the obstacle andthe like is determined based on the information acquired from the sensor1404. When the information about the singularity at which the distancevalues are discontinuous is generated, the determination of the obstaclemay be supplemented by the camera 1406 that acquires the two-dimensionalinformation.

In one example, when the determination of the obstacle is supplementedby the information acquired by the camera 1406, whether thecorresponding object is the obstacle is determined (S70). In the imageacquired by the camera 1406, the plurality of singularities may alsoexist identically or there is no object in the corresponding portion.Therefore, even when the information acquired by the camera 1406 isconsidered, it may be concluded that there are two cases: the case inwhich the obstacle exists and the case in which the obstacle does notexist.

When determining that the object is the obstacle, the controller 1800may use the machine learning technology to determine whether thecorresponding obstacle should be avoided or whether the correspondingobstacle is able to be simply passed.

In one example, in a case of a usual obstacle, the driver 1300 may bedriven such that the robot cleaner travels while avoiding the obstacleso as not to collide with the obstacle.

When the object is not determined as the obstacle in S70, a traveldirection of the robot cleaner may be set such that the robot cleanerpasses the object.

FIG. 7 is a view comparing images of a sensor and a camera captured arod.

In the same process as in FIG. 6 , the robot cleaner may accuratelydetermine whether there is an object, such as a rod, having a smallthickness compared to a length thereof in FIG. 7 .

(a) in FIG. 7 is a screen in which information acquired by the sensor1404 is image-processed by the controller 1800 to contain the distancevalue. in addition, (b) in FIG. 7 is a screen captured by the camera. Inthis connection, the camera 1406 is the two-dimensional camera, whichmay include the RGB camera or the IR camera.

In general, it is difficult to recognize the object such as the wire,the rod, or the like that having the small thickness compared to thelength thereof as the obstacle by the depth image. This is becausevarious noises and errors may occur in the process in which the imagesensed by the sensor is image-processed to contain the distance value.Therefore, the present embodiment provides a technology capable ofimproving a degree of recognition of the obstacle using thetwo-dimensional camera image in order to reduce the error of determiningthat the obstacle does not exist even though the obstacle exists.

The present disclosure may not be limited to the embodiment describedabove. As may be seen from the appended claims, the present disclosuremay be modified by a person having ordinary knowledge in the field towhich the present disclosure belongs, and such modification may belongto the scope of disclosure.

1. A method for controlling a robot cleaner, the method comprising:acquiring, by a camera, an image; irradiating, by a light source, lighttoward a location the same as a location where the acquired image iscaptured; receiving, by a sensor, the light irradiated from the lightsource and reflected on an object; processing an image received from thesensor to contain a distance value of an individual location; andsupplementing the image received from the sensor with the image capturedby the camera when a singularity is found, wherein distance valuescalculated in adjacent portions are discontinuous at the singularity. 2.The method of claim 1, wherein the camera captures a 2-dimensionalimage.
 3. The method of claim 2, wherein the camera is an RGB camera. 4.The method of claim 3, wherein the supplementing of the image receivedfrom the sensor with the image captured by the camera includes:connecting disconnected portions having the singularity interposedtherebetween with each other and determining the disconnected portionsas the same object when the disconnected portions are in the same color.5. The method of claim 2, wherein the camera is an IR camera.
 6. Themethod of claim 3, wherein the supplementing of the image received fromthe sensor with the image captured by the camera includes: connectingdisconnected portions having the singularity interposed therebetweenwith each other and determining the disconnected portions as the sameobject when the disconnected portions have the brightness.
 7. The methodof claim 1, wherein the supplementing of the image received from thesensor with the image captured by the camera includes: determining thatthere is an obstacle at a portion where the singularity exists whendisconnected portions having the singularity interposed therebetween areconnected to each other.
 8. The method of claim 7, wherein the robotcleaner travels while avoiding the obstacle.
 9. A robot cleanercomprising: a camera for acquiring an image; a light source forirradiating light toward a location the same as a location where theacquired image is captured; a sensor for sensing that the lightirradiated from the light source is reflected; and a controllerconfigured to process an image using the light sensed by the sensor tocalculate a distance value of an individual location in thecorresponding image, wherein the image is supplemented with the imageacquired by the camera when a singularity is found, wherein distancevalues calculated in adjacent portions are discontinuous at thesingularity.
 10. The robot cleaner of claim 9, wherein the cameracaptures a 2-dimensional image.
 11. The robot cleaner of claim 10,wherein the camera is an RGB camera.
 12. The robot cleaner of claim 11,wherein the controller is configured to connect disconnected portionshaving the singularity interposed therebetween with each other anddetermine the disconnected portions as the same object when thedisconnected portions are in the same color.
 13. The robot cleaner ofclaim 9, wherein the camera is an IR camera.
 14. The robot cleaner ofclaim 12, wherein the controller is configured to connect disconnectedportions having the singularity interposed therebetween with each otherand determine the disconnected portions as the same object when thedisconnected portions have the brightness.
 15. The robot cleaner ofclaim 9, wherein the controller is configured to determine that there isan obstacle at a portion where the singularity exists when the image issupplemented such that disconnected portions having the singularityinterposed therebetween are connected to each other.